Keras
65 reviews
- 1 profiles
- 1 categories
Average star rating
4.6
Serving customers since
2016
Keras Reviews
GS
GOURI S.
Technical Lead Data Scientist at ComvivaKeras deep learning API
What I liked the most about Keras framework is unlike tensorflow it provide easy set of code lines, using that we can develop deep learning model easily.
CM
Chandresh M.
System Engineer at TCS | AI | ML | AR | Learning EverydayFramework You Need for AI
The first thing I like about Keras is that it is a very user-friendly API. I can create Deep Learning models very quickly because of their very rich functions. Another important thing is its community. Whenever I find any problem in code then I can look for it in the Keras community; because of its popularity, you can find solutions a little bit easier. It also provides many pre-trained models like Xception, MobileNet, VGG16, InceptionV3, and many more. So I can use these models without training. If you have GPUs, then it also provides GPU support, which makes training of models faster.
DY
deniz y.
Business Intelligence Manager / Data & Insights ManagerEasy and successful
Neural networks are indispensable for data science and machine learning. It is quite easy to use if you have a little knowledge of the math of the job. The documentation and other resources are good and satisfying. The examples on keras.io are very instructive. The image processing module is successful. Runs models smoothly on GPU and CPU. It supports RNN and CNN.
About
What is Keras?
Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library, streamlining the process of building and training deep learning models with its high-level, user-friendly APIs. Designed to enable fast experimentation with deep neural networks, it focuses on being minimal, modular, and extensible. The website https://keras.io serves as a comprehensive resource for developers, offering detailed documentation, tutorials, and a community forum to help both beginners and experienced users in crafting state-of-the-art deep learning models efficiently.
Details
Year Founded
2016
Website
keras.io